Download Image analysis - JACC: Cardiovascular Imaging

ONLINE APPENDIX
Supplementary Methods
Pulse sequence parameters and CMR protocol
Cine imaging used a balanced steady-state free precession (bSSFP) pulse sequence (echo
time (TE)/repetition time (TR)/flip angle 1.3ms/2.6ms/40°, spatial resolution 1.6×2.0×10mm,
typical temporal resolution 25ms). Tissue tagging used a spatial modulation of magnetization
(SPAMM) pulse sequence (spatial resolution 1.5×1.5×10mm, tag separation 7mm, temporal
resolution ≤35ms, typical TR/TE/flip angle 5.9/3.5/10°). T2-weighted imaging used a darkblood T2w fast spin echo short tau inversion-recovery (STIR) sequence (TE 90 ms, TR two
R-R intervals, flip angle 90 degrees, spatial resolution 1.7×1.7×10 mm) and constant level
appearance (CLEAR) homogeneity correction. T1 mapping used a 17-heart MOLLI method
to acquire 11 images (3-3-5 acquisition with 3x R-R interval recovery epochs) in a single
end-expiratory breath hold (1,2) (bSSFP readout in end-diastole, manual RF shim
adjustments, 2x sensitivity-encoded (SENSE) acceleration, acquired spatial resolution
1.7×2.1×10mm, typical TE/TR/flip angle 2.7/1.06/35°). 0.1mmol/kg gadolinium-DTPA
(gadopentetate dimeglumine; Magnevist, Bayer, Berlin, Germany) was then administered
using a power injector (Spectris, Solaris, PA). Repeat MOLLI T1 mapping was performed at
15 minutes post-contrast, and LGE imaging at 16-20 minutes post contrast (inversion
recovery-prepared T1-weighted gradient echo, inversion time according to Look-Locker
scout, spatial resolution 1.54×1.75×10mm, TR/TE/flip angle 3.7/2.0/25°). In addition to the
three LGE short-axis slices for analysis, a contiguous stack of LGE images was acquired
immediately after the three slice LGE acquisition (imaging parameters as above, slice
thickness 10mm, no slice gap).
Image analysis
1
In addition to alignment of slices during image acquisition, accurate alignment of serial scans
was verified by comparing ventricular and papillary muscle morphology. Slices that were not
aligned between sequences or time-points were not analyzed. Left ventricular volumes and
ejection fraction (EF) were analyzed from cine images using standard methods. Infarct
location was determined by CMR, according to standard guidelines (3). MO was defined
visually as the hypointense core within the infarct zone on LGE imaging. A variety of LGE
thresholding techniques (including any hypointense core) for identification of infarcted
myocardium were compared for segmental analysis, namely 2, 5 and 6 standard deviations
(SD), visual infarct delineation (blinded to the results of other threshold techniques), fullwidth at half maximum (FWHM) and a histogram-based automated threshold technique
(Otsu) (4). Infarcted myocardium defined as LGE hyperenhancement ≥5 standard deviations
(SD) above remote myocardium and including any hypointense core was chosen for further
comparisons as it had the highest c-statistic for prediction of recovery of segmental function.
Infarct size and MO were measured from LGE images. Infarct volumes were calculated
across the whole LV stack by the modified Simpson’s method.
LGE transmural extent chord data were averaged into either 16-segments for the segmental
analysis, or averaged across the infarct zone for per-patient analysis. Segmental analysis for
improvement in function included only those segments that were dysfunctional (wall motion
score ≥1) acutely. Remote myocardium was selected as a 60° sector diametrically opposing
the infarct and in an area without LGE. LGE signal intensity was analyzed from the scannergenerated DICOM images, with the signal intensity obtained as a mean of the infarct zone
using the same region of interest as in the per-patient analysis, and recorded in arbitrary units
as generated by cvi42 analysis software.
ECV was calculated for infarct and remote zones using the following equation, where R1 is
the reciprocal of T1 (5):
2
𝐸𝐶𝑉 = (1 − ℎ𝑒𝑚𝑎𝑡𝑜𝑐𝑟𝑖𝑡) ×
𝑅1𝑚𝑦𝑜 𝑝𝑜𝑠𝑡 − 𝑅1𝑚𝑦𝑜 𝑝𝑟𝑒
𝑅1𝑏𝑙𝑜𝑜𝑑 𝑝𝑜𝑠𝑡 − 𝑅1𝑏𝑙𝑜𝑜𝑑 𝑝𝑟𝑒
T1 and ECV normal reference ranges for our center/sequence have been published previously
(6).
Strain was measured in the single short-axis slice that demonstrated maximal infarction on
LGE imaging. The same position was analyzed for the convalescent scan. Area at risk was
measured from T2-weighted imaging, with delineation of edematous myocardium using the
full-width at half maximum threshold technique. Myocardial salvage index was calculated
using the formula: myocardial salvage index = (area at risk – infarct volume) / area at risk.
Statistical analysis
Differences in segmental measurements were evaluated using a multilevel linear mixedeffects model to account for non-independence of segmental data; r denotes partial
correlation in this context. A sample size of 35 patients was calculated (7) to detect a 10%
difference in accuracy (AUC) with power 80% at a significance level of 0.05, assuming rank
correlation of 0.55 between ECV and transmural extent of LGE, accuracy of LGE as 0.82,
artefact in 15% of segments, and one-third of segments dysfunctional acutely (8). Normality
for quantitative data was established using the Kolmogorov-Smirnov test. Univariable
analyses were performed to identify predictors of reduced strain and EF at 90 days. Variables
with a probability value <0.1 in the univariable analysis were included in a multivariable
linear regression analysis. Receiver operating characteristic (ROC) curves were compared
using the method described by DeLong et al. (9) The optimal cut point for ECV imaging was
determined from the ROC curve (Figure 5) using Youden’s index (10).
3
Supplementary Results
Patient Recruitment
Of 90 eligible patients admitted within the recruitment period, 13 had obesity that precluded
CMR, 4 were unable to lie flat, 1 had an MR-incompatible pacemaker, 14 were unable to
consent and 5 were due CABG prior to the follow-up scan. The remaining 53 patients were
approached, of which 9 declined to participate. Therefore 44 patients constituted the study
sample. 5 did not attend follow-up. 39 patients therefore completed baseline and follow up
scans and were included in the statistical analysis. 18 slices (15%) did not have good
alignment between methods and/or time-points and were excluded from analysis. 7 segments
in segmental analysis (all remote) were excluded as R2 for T1 mapping was <0.95. All
regions in the per-patient analysis had R2≥0.95.
4
Supplementary References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Messroghli DR, Radjenovic A, Kozerke S, Higgins DM, Sivananthan MU, Ridgway
JP. Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1
mapping of the heart. Magn Reson Med 2004;52:141-6.
Messroghli DR, Walters K, Plein S et al. Myocardial T1 mapping: application to
patients with acute and chronic myocardial infarction. Magn Reson Med 2007;58:3440.
Cerqueira MD, Weissman NJ, Dilsizian V et al. Standardized myocardial
segmentation and nomenclature for tomographic imaging of the heart. A statement for
healthcare professionals from the Cardiac Imaging Committee of the Council on
Clinical Cardiology of the American Heart Association. Circulation 2002;105:539-42.
Otsu N. A Threshold Selection Method from Gray-Level Histograms. Systems, Man
and Cybernetics, IEEE Transactions on 1979;9:62-66.
Miller CA, Naish JH, Bishop P et al. Comprehensive validation of cardiovascular
magnetic resonance techniques for the assessment of myocardial extracellular volume.
Circ Cardiovasc Imaging 2013;6:373-83.
Dabir D, Child N, Kalra A et al. Reference values for healthy human myocardium
using a T1 mapping methodology: results from the International T1 Multicenter
cardiovascular magnetic resonance study. J Cardiovasc Magn Reson 2014;16:69.
Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating
characteristic curves derived from the same cases. Radiology 1983;148:839-43.
Romero J, Kahan J, Kelesidis I et al. CMR imaging for the evaluation of myocardial
stunning after acute myocardial infarction: a meta-analysis of prospective trials. Eur
Heart J Cardiovasc Imaging 2013;14:1080-91.
DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or
more correlated receiver operating characteristic curves: a nonparametric approach.
Biometrics 1988;44:837-45.
Youden WJ. Index for rating diagnostic tests. Cancer 1950;3:32-5.
5
Supplementary Figures
Figure 1. Comparison of ECV with LGE transmural extent by quartiles. Data presented are
per-segment.
6
Figure 2. Prediction of improvement in convalescent wall motion score for each quartile of
acute LGE transmural extent, using a cut-off value of 0.5 for acute ECV. Segmental analysis
of dysfunctional segments only (n=163). The first bar in each quartile represents patients with
ECV <0.5; the second bar represents ECV >0.5.
7